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Student-t kernelized fuzzy rough set model with ...
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由 X Yang 著作2022被引用 22 次 — The new model uses fuzzy divergence to evaluate uncertain information in the data. It also explores a newly-defined feature evaluation function on the biases of ...
Student-t kernelized fuzzy rough set model with fuzzy ...
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由 X Yang 著作2022被引用 22 次 — The new model uses fuzzy divergence to evaluate uncertain information in the data. It also explores a newly-defined feature evaluation function on the biases of ...
Student-t Kernelized Fuzzy Rough Set Model with ...
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The new model uses fuzzy divergence to evaluate uncertain information in the data. It also explores a newly-defined feature evaluation function on the biases of ...
Student-t kernelized fuzzy rough set model with fuzzy divergence ...
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Semantic Scholar extracted view of "Student-t kernelized fuzzy rough set model with fuzzy divergence for feature selection" by Xiaoling Yang et al.
Student-t kernelized fuzzy rough set model with fuzzy ...
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由 X Yang 著作2022被引用 22 次 — The new model uses fuzzy divergence to evaluate uncertain information in the data. It also explores a newly-defined feature evaluation function ...
Student-t kernelized fuzzy rough set model with fuzzy divergence ...
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Fuzzy rough set theory can tackle feature redundancy in data and select more informative features for machine learning tasks. Gaussian kernel is often ...
Fuzzy rough feature selection based on normalized conditional ...
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It selects a set of features by maximizing the relevance and significance of the selected features. An improvement is made by normalized conditional mutual ...
Pengfei Zhang (张鹏飞
Google
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Student-t kernelized fuzzy rough set model with fuzzy divergence for feature selection. X Yang, H Chen, T Li, P Zhang, C Luo. Information Sciences 610, 52-72 ...
Feature Selection With Local Density-Based Fuzzy Rough Set ...
R Discovery
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R Discovery
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Fuzzy rough set theory can model uncertainty in data and has been applied to feature selection for machine learning tasks. The existence of noise in data is ...
Hybrid similarity relation based mutual information for ...
Nature
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由 AK Tiwari 著作2024被引用 5 次 — Fuzzy rough mutual information has been presented by integrating information entropy with fuzzy rough set to measure the importance of features.